Combining phylogeny and coevolution improves the inference of interaction partners among paralogous proteins

TL;DR

This paper presents a combined approach using phylogeny and coevolution signals to improve the prediction of interaction partners among paralogous proteins, especially in complex cases with many paralogs or limited data.

Contribution

The study introduces a novel method that integrates phylogenetic alignment with coevolution analysis to enhance interaction partner inference among paralogs.

Findings

Combined method outperforms individual approaches.

Significant improvements in complex scenarios with many paralogs.

Effective even with limited sequence data.

Abstract

Predicting protein-protein interactions from sequences is an important goal of computational biology. Various sources of information can be used to this end. Starting from the sequences of two interacting protein families, one can use phylogeny or residue coevolution to infer which paralogs are specific interaction partners within each species. We show that these two signals can be combined to improve the performance of the inference of interaction partners among paralogs. For this, we first align the sequence-similarity graphs of the two families through simulated annealing, yielding a robust partial pairing. We next use this partial pairing to seed a coevolution-based iterative pairing algorithm. This combined method improves performance over either separate method. The improvement obtained is striking in the difficult cases where the average number of paralogs per species is large or where the total number of sequences is modest.